Opportunities and challenges in application of artificial intelligence in pharmacology.

Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a huge amount of medical data every day. Therefore, we need an automated and reliable evaluation tool that can make decisions more accurately and faster. Machine learning has the potential to learn, understand and analyse the data used in healthcare systems. In the last few years, AI is known to be employed in various fields in pharmaceutical science especially in pharmacological research. It helps in the analysis of preclinical (laboratory animals) and clinical (in human) trial data. AI also plays important role in various processes such as drug discovery/manufacturing, diagnosis of big data for disease identification, personalized treatment, clinical trial research, radiotherapy, surgical robotics, smart electronic health records, and epidemic outbreak prediction. Moreover, AI has been used in the evaluation of biomarkers and diseases. In this review, we explain various models and general processes of machine learning and their role in pharmacological science. Therefore, AI with deep learning and machine learning could be relevant in pharmacological research.

MicroRNA Alteration, Application as Biomarkers, and Therapeutic Approaches in Neurodegenerative Diseases.

MicroRNAs (miRNAs) are essential post-transcriptional gene regulators involved in various neuronal and non-neuronal cell functions and play a key role in pathological conditions. Numerous studies have demonstrated that miRNAs are dysregulated in major neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, or Huntington's disease. Hence, in the present work, we constructed a comprehensive overview of individual microRNA alterations in various models of the above neurodegenerative diseases. We also provided evidence of miRNAs as promising biomarkers for prognostic and diagnostic approaches. In addition, we summarized data from the literature about miRNA-based therapeutic applications via inhibiting or promoting miRNA expression. We finally identified the overlapping miRNA signature across the diseases, including miR-128, miR-140-5p, miR-206, miR-326, and miR-155, associated with multiple etiological cellular mechanisms. However, it remains to be established whether and to what extent miRNA-based therapies could be safely exploited in the future as effective symptomatic or disease-modifying approaches in the different human neurodegenerative disorders.

Blocking glutamate mGlu5 receptors with the negative allosteric modulator CTEP improves disease course in SOD1G93A mouse model of amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: The pathogenesis of amyotrophic lateral sclerosis (ALS) is not fully clarified, although excessive glutamate (Glu) transmission and the downstream cytotoxic cascades are major mechanisms for motor neuron death. Two metabotropic glutamate receptors (mGlu1 and mGlu5 ) are overexpressed in ALS and regulate cellular disease processes. Expression and function of mGlu5 receptors are altered at early symptomatic stages in the SOD1G93A mouse model of ALS and knockdown of mGlu5 receptors in SOD1G93A mice improved disease progression. EXPERIMENTAL APPROACH: We treated male and female SOD1G93A mice with 2-chloro-4-((2,5-dimethyl-1-(4-(trifluoromethoxy)phenyl)-1H-imidazol-4-yl)ethynyl)pyridine (CTEP), an orally available mGlu5 receptor negative allosteric modulator (NAM), using doses of 2 mg·kg-1 per 48 h or 4 mg·kg-1 per 24 h from Day 90, an early symptomatic disease stage. Disease progression was studied by behavioural and histological approaches. KEY RESULTS: CTEP dose-dependently ameliorated clinical features in SOD1G93A mice. The lower dose increased survival and improved motor skills in female mice, with barely positive effects in male mice. Higher doses significantly ameliorated disease symptoms and survival in both males and females, females being more responsive. CTEP also reduced motor neuron death, astrocyte and microglia activation, and abnormal glutamate release in the spinal cord, with equal effects in male and female mice. No differences were also observed in CTEP access to the brain. CONCLUSION AND IMPLICATIONS: Our results suggest that mGlu5 receptors are promising targets for the treatment of ALS and highlight mGlu5 receptor NAMs as effective pharmacological tools with translational potential.